Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
1902.00621
Cited By
v1
v2
v3
v4 (latest)
On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning
International Conference on Learning Representations (ICLR), 2019
2 February 2019
Jian Li
Xuanyuan Luo
Mingda Qiao
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning"
50 / 65 papers shown
Enhancing Generalization in Data-free Quantization via Mixup-class Prompting
Jiwoong Park
Chaeun Lee
Yongseok Choi
Sein Park
Deokki Hong
Jungwook Choi
MQ
210
0
0
29 Jul 2025
Generalization Bound of Gradient Flow through Training Trajectory and Data-dependent Kernel
Yilan Chen
Zhichao Wang
Wei Huang
Andi Han
Taiji Suzuki
Arya Mazumdar
MLT
232
1
0
12 Jun 2025
Generalization in VAE and Diffusion Models: A Unified Information-Theoretic Analysis
International Conference on Learning Representations (ICLR), 2025
Qi Chen
Jierui Zhu
Florian Shkurti
DiffM
266
2
0
01 Jun 2025
Information-theoretic Generalization Analysis for VQ-VAEs: A Role of Latent Variables
Futoshi Futami
Masahiro Fujisawa
DRL
CML
412
0
0
26 May 2025
Temperature is All You Need for Generalization in Langevin Dynamics and other Markov Processes
I. Harel
Yonathan Wolanowsky
Gal Vardi
Nathan Srebro
Daniel Soudry
AI4CE
423
2
0
25 May 2025
NeuralGrok: Accelerate Grokking by Neural Gradient Transformation
Xinyu Zhou
Simin Fan
Martin Jaggi
Jie Fu
261
1
0
24 Apr 2025
Randomized Pairwise Learning with Adaptive Sampling: A PAC-Bayes Analysis
Sijia Zhou
Yunwen Lei
Ata Kabán
367
0
0
03 Apr 2025
Stability-based Generalization Analysis of Randomized Coordinate Descent for Pairwise Learning
AAAI Conference on Artificial Intelligence (AAAI), 2025
Liang Wu
Ruixi Hu
Yunwen Lei
286
0
0
03 Mar 2025
Towards Auto-Regressive Next-Token Prediction: In-Context Learning Emerges from Generalization
International Conference on Learning Representations (ICLR), 2025
Zixuan Gong
Xiaolin Hu
Huayi Tang
Yong Liu
334
2
0
24 Feb 2025
Stability-based Generalization Bounds for Variational Inference
Yadi Wei
Roni Khardon
BDL
268
0
0
17 Feb 2025
Understanding the Generalization Error of Markov algorithms through Poissonization
Benjamin Dupuis
Maxime Haddouche
George Deligiannidis
Umut Simsekli
301
1
0
11 Feb 2025
Understanding Generalization of Federated Learning: the Trade-off between Model Stability and Optimization
Dun Zeng
Zheshun Wu
Shiyu Liu
Yu Pan
Xiaoying Tang
Zenglin Xu
MLT
FedML
529
2
0
25 Nov 2024
Stability and Sharper Risk Bounds with Convergence Rate
O
~
(
1
/
n
2
)
\tilde{O}(1/n^2)
O
~
(
1/
n
2
)
Bowei Zhu
Shaojie Li
Mingyang Yi
Yong Liu
289
1
0
13 Oct 2024
When Foresight Pruning Meets Zeroth-Order Optimization: Efficient Federated Learning for Low-Memory Devices
Peng Zhang
Yingjie Liu
Yingbo Zhou
Xiao Du
Xian Wei
Ting Wang
Xiao He
FedML
229
3
0
08 May 2024
Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets
Benjamin Dupuis
Paul Viallard
George Deligiannidis
Umut Simsekli
344
6
0
26 Apr 2024
Leveraging Gradients for Unsupervised Accuracy Estimation under Distribution Shift
Renchunzi Xie
Ambroise Odonnat
Vasilii Feofanov
I. Redko
Jianfeng Zhang
Bo An
UQCV
444
2
0
17 Jan 2024
Information-Theoretic Generalization Bounds for Transductive Learning and its Applications
Huayi Tang
Yong Liu
517
3
0
08 Nov 2023
Time-Independent Information-Theoretic Generalization Bounds for SGLD
Neural Information Processing Systems (NeurIPS), 2023
Futoshi Futami
Masahiro Fujisawa
360
12
0
02 Nov 2023
Generalization Bounds for Label Noise Stochastic Gradient Descent
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Jung Eun Huh
Patrick Rebeschini
351
2
0
01 Nov 2023
Sample-Conditioned Hypothesis Stability Sharpens Information-Theoretic Generalization Bounds
Neural Information Processing Systems (NeurIPS), 2023
Ziqiao Wang
Yongyi Mao
299
7
0
31 Oct 2023
Minibatch and Local SGD: Algorithmic Stability and Linear Speedup in Generalization
Yunwen Lei
Tao Sun
Mingrui Liu
473
4
0
02 Oct 2023
Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent
Neural Information Processing Systems (NeurIPS), 2023
Lingjiong Zhu
Mert Gurbuzbalaban
Anant Raj
Umut Simsekli
274
7
0
20 May 2023
Select without Fear: Almost All Mini-Batch Schedules Generalize Optimally
Konstantinos E. Nikolakakis
Amin Karbasi
Dionysis Kalogerias
326
7
0
03 May 2023
Machine Learning and the Future of Bayesian Computation
Steven Winter
Trevor Campbell
Lizhen Lin
Sanvesh Srivastava
David B. Dunson
TPM
370
6
0
21 Apr 2023
Does Federated Learning Really Need Backpropagation?
European Conference on Computer Vision (ECCV), 2023
Hao Feng
Tianyu Pang
Chao Du
Wei Chen
Shuicheng Yan
Min Lin
FedML
286
13
0
28 Jan 2023
Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization
International Conference on Algorithmic Learning Theory (ALT), 2022
Mahdi Haghifam
Borja Rodríguez Gálvez
Ragnar Thobaben
Mikael Skoglund
Daniel M. Roy
Gintare Karolina Dziugaite
355
20
0
27 Dec 2022
On the Importance of Gradient Norm in PAC-Bayesian Bounds
Neural Information Processing Systems (NeurIPS), 2022
Itai Gat
Yossi Adi
Alex Schwing
Tamir Hazan
BDL
289
6
0
12 Oct 2022
Exploring the Algorithm-Dependent Generalization of AUPRC Optimization with List Stability
Neural Information Processing Systems (NeurIPS), 2022
Peisong Wen
Qianqian Xu
Zhiyong Yang
Yuan He
Qingming Huang
313
15
0
27 Sep 2022
Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks
Neural Information Processing Systems (NeurIPS), 2022
Yunwen Lei
Rong Jin
Yiming Ying
MLT
296
24
0
19 Sep 2022
Generalization Bounds for Stochastic Gradient Descent via Localized
ε
\varepsilon
ε
-Covers
Neural Information Processing Systems (NeurIPS), 2022
Sejun Park
Umut Simsekli
Murat A. Erdogdu
214
10
0
19 Sep 2022
Max-Margin Works while Large Margin Fails: Generalization without Uniform Convergence
International Conference on Learning Representations (ICLR), 2022
Margalit Glasgow
Colin Wei
Mary Wootters
Tengyu Ma
349
5
0
16 Jun 2022
Stability and Generalization of Stochastic Optimization with Nonconvex and Nonsmooth Problems
Annual Conference Computational Learning Theory (COLT), 2022
Yunwen Lei
281
27
0
14 Jun 2022
Generalization Bounds for Gradient Methods via Discrete and Continuous Prior
Neural Information Processing Systems (NeurIPS), 2022
Jun Yu Li
Xu Luo
Jian Li
308
4
0
27 May 2022
Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD
International Conference on Learning Representations (ICLR), 2022
Konstantinos E. Nikolakakis
Farzin Haddadpour
Amin Karbasi
Dionysios S. Kalogerias
482
22
0
26 Apr 2022
Sharper Utility Bounds for Differentially Private Models
International Conference on Information and Knowledge Management (CIKM), 2022
Yilin Kang
Yong Liu
Jian Li
Weiping Wang
FedML
233
3
0
22 Apr 2022
On the Generalization Mystery in Deep Learning
S. Chatterjee
Piotr Zielinski
OOD
312
45
0
18 Mar 2022
Confidence Dimension for Deep Learning based on Hoeffding Inequality and Relative Evaluation
Runqi Wang
Linlin Yang
Baochang Zhang
Wentao Zhu
David Doermann
Guodong Guo
157
1
0
17 Mar 2022
Black-Box Generalization: Stability of Zeroth-Order Learning
Neural Information Processing Systems (NeurIPS), 2022
Konstantinos E. Nikolakakis
Farzin Haddadpour
Dionysios S. Kalogerias
Amin Karbasi
MLT
230
2
0
14 Feb 2022
Towards Data-Algorithm Dependent Generalization: a Case Study on Overparameterized Linear Regression
Neural Information Processing Systems (NeurIPS), 2022
Jing Xu
Jiaye Teng
Yang Yuan
Andrew Chi-Chih Yao
415
3
0
12 Feb 2022
Stability Based Generalization Bounds for Exponential Family Langevin Dynamics
International Conference on Machine Learning (ICML), 2022
A. Banerjee
Tiancong Chen
Xinyan Li
Yingxue Zhou
310
9
0
09 Jan 2022
Associative Adversarial Learning Based on Selective Attack
Runqi Wang
Xiaoyue Duan
Baochang Zhang
Shenjun Xue
Wentao Zhu
David Doermann
G. Guo
AAML
279
0
0
28 Dec 2021
Generalization Bounds for Stochastic Gradient Langevin Dynamics: A Unified View via Information Leakage Analysis
Bingzhe Wu
Zhicong Liang
Yatao Bian
Chaochao Chen
Junzhou Huang
Yuan Yao
126
1
0
14 Dec 2021
Time-independent Generalization Bounds for SGLD in Non-convex Settings
Tyler Farghly
Patrick Rebeschini
227
28
0
25 Nov 2021
Optimizing Information-theoretical Generalization Bounds via Anisotropic Noise in SGLD
Bohan Wang
Huishuai Zhang
Jieyu Zhang
Qi Meng
Wei Chen
Tie-Yan Liu
133
1
0
26 Oct 2021
What Happens after SGD Reaches Zero Loss? --A Mathematical Framework
Zhiyuan Li
Tianhao Wang
Sanjeev Arora
MLT
427
115
0
13 Oct 2021
Stochastic Anderson Mixing for Nonconvex Stochastic Optimization
Fu Wei
Chenglong Bao
Yang Liu
211
25
0
04 Oct 2021
Generalization Bounds For Meta-Learning: An Information-Theoretic Analysis
Qi Chen
Changjian Shui
M. Marchand
247
59
0
29 Sep 2021
Generalization Bounds using Lower Tail Exponents in Stochastic Optimizers
Liam Hodgkinson
Umut Simsekli
Rajiv Khanna
Michael W. Mahoney
329
27
0
02 Aug 2021
Improved Learning Rates for Stochastic Optimization: Two Theoretical Viewpoints
Shaojie Li
Yong Liu
340
14
0
19 Jul 2021
Towards Understanding Generalization via Decomposing Excess Risk Dynamics
International Conference on Learning Representations (ICLR), 2021
Jiaye Teng
Jianhao Ma
Yang Yuan
269
6
0
11 Jun 2021
1
2
Next
Page 1 of 2
